Big wave of massive job creation heading our way

Big wave riders are crazy! Being towed by a jet ski only to be let go in front of a 50 ft monster wave is not everyones’ idea of fun. One of these waves can plunge a surfer 15m below the surface, spinning them around like an industrial strength washing machine — leaving the surfer struggling to work out which way is up.

But being held underwater by two or more consecutive waves is probably more like the heavy duty spin cycle. And yet, for some crazies, the Monster Wave is the ultimate opportunity. Just like when you were that nervously excited kid riding their first wave — albeit the ‘monsters’ were only slightly above your head.

Current disruption to the world of work is like a set of big waves — but alarmist news headlines forgot to mention the massive wave of job creation coming our way! So, cut yourself some slack for believing the common dystopian line, and fast forward to your morning espresso to think clearly about the future of work.

Two waves

Zooming out I can see two waves — massive job destruction and massive job creation. As Wave 1 breaks on the labour market and pushes toward the automation of jobs, Wave 2 will create new jobs and industries.

No one knows the distance between the two waves or the precise speed at which they’re travelling. But there’s plenty of fake news!

Truth is, we are going to see rapid job churn, moving out of one occupational category and into another. Which, by the way, is nothing new. Horse and buggy, Model T Ford and autonomous vehicles are the obvious examples. For a sensible explanation of job churn, check out David Autor’s (2015), Why are there still so many jobs, the history and future of workplace automation.

Automation also complements labor, raises output in ways that leads to higher demand for labor, and interacts with adjustments in labor supply (Autor 2015).

Wave 1 — Massive job destruction

I said it: ‘massive job destruction’. We are witnessing astounding innovation in the production process — widespread automation and emerging AI.

The automation of banking jobs is said to increase by 30% between 2015 and 2025, mainly due to retail banking automation. But while that’s true, the impact of Wave 1 will be patchy and difficult to predict. A recent study found that only 1 in 20 companies have extensively incorporated AI into their processes.

Some jobs are more easily automated, particularly those with routinised tasks, while non-routine tasks tend to be more resistant. This is creating new opportunities for early adopters, while some companies cling to business as usual.

Modelling on US occupational categories has predicted that up to 47% of jobs in advanced economies may be replaced by technology in the next two decades. However, OECD research found that only 9% of jobs are at high risk of being automated. Regarding AI, Erik Brynjolfsson, from MIT argues, “AI won’t be able to replace most jobs anytime soon. But in almost every industry, people using AI are starting to replace people who don’t use AI, and that trend will only accelerate.” Not every one will build AI products, or even want to (I don’t), but we will all need to learn how to use it.

It just occurred to me, what’s AI 2.0? — perhaps Blended Intelligence (BI) def. — the right mix of human and artificial intelligence to maximise customer engagement (okay, I just made that up). Behold, there will be new jobs working in the BI industry.

The point is, life long learning is not negotiable for the modern worker.

Wave 2— Massive job creation

I said it, along with just a few others: ‘massive job creation’. Wave 2 has been hidden behind Wave 1 and is gaining momentum. Seriously, with all the focus on innovation and design there will be the creation of completely new products and services.

We have already witnessed Wave 1 and Wave 2 in the application of ‘wearables’ to health and medical, fashion, infotainment and the military — predicted to be worth $34 billion by 2020. The ‘old school’ fitness trainer job has been fragmented by automation (Wave 1), which has in turn (or in-churn) created new jobs, and a whole new industry.

No doubt some pimply kid beavering away in his parent’s garage will invent the next big thing. Unintentionally, he will also enable massive job creation and new industries. We already have the platform ecosystems to connect skilled workers with inventors to rapidly scale new industries. The future workforce will be on-demand and everywhere.

Warning!! Big public and private sector organisations who isolate themselves from platform ecosystems won’t survive — they will be dis-intermediated by startup ‘garage boy’ in partnership with his favourite platform. Okay, maybe garage boy actually works for Google, but you get the point.

So what would you have me do?

Introducing Occupational Forecasting (OF)

The biggest mistake I currently see thought leaders making is using a narrow lens to understand the impact of automation on human capital outlook.

The future of work is complex and multifaceted. Which is why every organisation urgently needs what I’ve called Occupational Forecasting (OF) — a technique for (1)understanding the impact factors on an occupation, and (2) developing occupation scenarios.

Step 1 — Map four impact factors:

• Demand- local and global demand for an occupation.
• Supply- local and global supply for an occupation.
• Skills- local and global shortages, clusters and portability of a given occupation.
• Environment- megatrends, emerging tech, and government interventions for an occupation.

Step 2 — Validate via local data collection methods, such as:

• Survey workers about their perspective on occupation outlook.
• Interview experts about their perspective on occupation outlook.
• Synthesise the data from Step 1 and Step 2 for each occupation.

Step 3— Develop occupation scenarios, for example:

• If the impact of Wave 1 on your organisation (industry) is likely to be high, and the probability of that occurring is also high — your decision time is short, its time to innovate.
• Whereas, if the impact is likely to be high, but the probability of that occurring is low — your decision time is longer, weigh your options.

Occupational Forecasting is not a way to predict the future, but it can help you make better decisions and harness opportunities for the future of work.

If you want help working out what’s next for your organisation, contact me at the Chair in Digital Economy.

Dr Matthew Flynn | Theme leader, Future of Work | m6.flynn@qut.edu.au